Timothy Supinie;
Youngsun Jung;
Nusrat Yussouf;
Ming Xue
Center for Analysis and Prediction of Storms
The 8th EnKF Data Assimilation Workshop
Assimilation of Phased Array Radar Data with the 4-Dimensional Ensemble Kalman Filter
Talk:
Supinie_EnKFWorkshop2018_TAS.pptx
The goal of the Warn on Forecast (WoF) project is to provide increased lead time for hazardous weather warnings by basing warnings on NWP output. Meeting this goal requires good model initializations at storm scales, a task for which radar data is well-suited. Phased Array Radar (PAR) is a promising upcoming source of observations for storm-scale data assimilation. The main difference between PAR and current WSR-88D technology is that the beam of a PAR is electronically steered, allowing for more rapid data gathering. For example, a PAR can complete a full volume scan in 1 minute, compared to 4.5 minutes for a WSR-88D volume scan. Concurrently, the Spectrum Efficient National Surveillance Radar (SENSR) program is aiming to address weather and aircraft surveillance requirements simultaneously by consolidating weather, air traffic, and defense radar networks into a single system. PAR is a promising option for this replacement network.
Under the support of the WoF and SENSR projects, CAPS has been working with the National Severe Storms Laboratory (NSSL) to evaluate the impact of high temporal frequency observations available from PAR on the prediction of rapidly-developing convective hazards, such as tornadoes, severe winds, large hail, and flash flooding. We set up several ensemble data assimilation and forecast experiments using 36 members at 1 km grid spacing using data from the 31 May 2013 Oklahoma tornado and flash flood event. The Weather Research and Forecasting (WRF) model and Center for Analysis and Prediction of Storms (CAPS) 4D Ensemble Kalman Filter are used as the prediction model and data assimilation algorithm. An experiment assimilating PAR observations from the National Weather Radar Testbed research PAR is compared to an experiment assimilating WSR-88D observations. Several 1-hour forecasts are run to evaluate the effect of the different observations on the placement of heavy rainfall and supercell mesocyclones. Results of these forecasts will be discussed.
The goal of the Warn on Forecast (WoF) project is to provide increased lead time for hazardous weather warnings by basing warnings on NWP output. Meeting this goal requires good model initializations at storm scales, a task for which radar data is well-suited. Phased Array Radar (PAR) is a promising upcoming source of observations for storm-scale data assimilation. The main difference between PAR and current WSR-88D technology is that the beam of a PAR is electronically steered, allowing for more rapid data gathering. For example, a PAR can complete a full volume scan in 1 minute, compared to 4.5 minutes for a WSR-88D volume scan. Concurrently, the Spectrum Efficient National Surveillance Radar (SENSR) program is aiming to address weather and aircraft surveillance requirements simultaneously by consolidating weather, air traffic, and defense radar networks into a single system. PAR is a promising option for this replacement network.
Under the support of the WoF and SENSR projects, CAPS has been working with the National Severe Storms Laboratory (NSSL) to evaluate the impact of high temporal frequency observations available from PAR on the prediction of rapidly-developing convective hazards, such as tornadoes, severe winds, large hail, and flash flooding. We set up several ensemble data assimilation and forecast experiments using 36 members at 1 km grid spacing using data from the 31 May 2013 Oklahoma tornado and flash flood event. The Weather Research and Forecasting (WRF) model and Center for Analysis and Prediction of Storms (CAPS) 4D Ensemble Kalman Filter are used as the prediction model and data assimilation algorithm. An experiment assimilating PAR observations from the National Weather Radar Testbed research PAR is compared to an experiment assimilating WSR-88D observations. Several 1-hour forecasts are run to evaluate the effect of the different observations on the placement of heavy rainfall and supercell mesocyclones. Results of these forecasts will be discussed.
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